Development of a Quantitative Method for Detection of Multiclass Veterinary Drugs in Feed Using Modified QuPPe Extraction and LC–MS/MS

A method was developed for the rapid and quantitative analysis of 30 veterinary drugs belonging to 17 classes (amphenicols (1), anthelmintics (1), cephalosporins (4), coccidiostats (1), lincosamides (1), macrolide (1), nitroimidazole (1), penicillins (3), phenylhydrazines (1), polypeptides (1), pyrethrins (1), quinolones (5), sulfonamides (3), tetracycline (3), neuroleptic agents (1), triazene trypanocidal agents (1), other. (1)) in feeds. The proposed method with a modified Quick Polar Pesticides (QuPPe) sample preparation was validated for the determination of 30 veterinary drugs in feed samples by liquid chromatography triple-quadrupole mass spectrometry (LC–MS/MS). The sample was extracted with methanol containing 1% acetic acid and purified by dispersive solid-phase extraction (d-SPE) with C18. Good linearity (r² ≥ 0.98) was observed, and the LOQ values ranged from 10 to 200 µg/kg. Average recoveries ranged from 70.8 to 118.4%, and the relative standard deviation was ≤ 18.7%. This validated method was used in the determination of 30 veterinary drugs in 142 feed samples obtained from South Korea. The results show that lincomycin was present in only one of the tested feed samples, although it was detected at a value lower than the LOQ. In conclusion, this multi-residue method can be used for screening through the detection and quantitation of residual multiclass veterinary drugs in feed samples.     

In Silico Drug Repurposing of FDA-Approved Drugs Highlighting Promacta as a Potential Inhibitor of H7N9 Influenza Virus

Influenza virus infections continue to be a significant and recurrent public health problem. Although vaccine efficacy varies, regular immunisation is the most effective method for suppressing the influenza virus. Antiviral drugs are available for influenza, although two of the four FDA-approved antiviral treatments have resulted in significant drug resistance. Therefore, new treatments are being sought to reduce the burden of flu-related illness. The time-consuming development of treatments for new and re-emerging diseases such as influenza and the high failure rate are increasing concerns. In this context, we used an in silico-based drug repurposing method to repurpose FDA-approved drugs as potential therapies against the H7N9 virus. To find potential inhibitors, a total of 2568 drugs were screened. Promacta, tucatinib, and lurasidone were identified as promising hits in the DrugBank database. According to the calculations of MM-GBSA, tucatinib (−54.11 kcal/mol) and Promacta (−56.20 kcal/mol) occupied the active site of neuraminidase with a higher binding affinity than the standard drug peramivir (−49.09 kcal/mol). Molecular dynamics (MD) simulation studies showed that the C-α atom backbones of the complexes of tucatinib and Promacta neuraminidase were stable throughout the simulation period. According to ADME analysis, the hit compounds have a high gastrointestinal absorption (GI) and do not exhibit properties that allow them to cross the blood–brain barrier (BBB). According to the in silico toxicity prediction, Promacta is not cardiotoxic, while lurasidone and tucatinib show only weak inhibition. Therefore, we propose to test these compounds experimentally against the influenza H7N9 virus. The investigation and validation of these potential H7N9 inhibitors would be beneficial in order to bring these compounds into clinical settings.     

Open-Source Browser-Based Tools for Structure-Based Computer-Aided Drug Discovery

We here outline the importance of open-source, accessible tools for computer-aided drug discovery (CADD). We begin with a discussion of drug discovery in general to provide context for a subsequent discussion of structure-based CADD applied to small-molecule ligand discovery. Next, we identify usability challenges common to many open-source CADD tools. To address these challenges, we propose a browser-based approach to CADD tool deployment in which CADD calculations run in modern web browsers on users’ local computers. The browser app approach eliminates the need for user-initiated download and installation, ensures broad operating system compatibility, enables easy updates, and provides a user-friendly graphical user interface. Unlike server apps—which run calculations “in the cloud” rather than on users’ local computers—browser apps do not require users to upload proprietary information to a third-party (remote) server. They also eliminate the need for the difficult-to-maintain computer infrastructure required to run user-initiated calculations remotely. We conclude by describing some CADD browser apps developed in our lab, which illustrate the utility of this approach. Aside from introducing readers to these specific tools, we are hopeful that this review highlights the need for additional browser-compatible, user-friendly CADD software.     

锂离子电池硅基负极材料的研究进展

硅基材料是新一代高容量锂离子蓄电池负极材料的典型代表,近年来已成为理论研究和应用研究的热点.本文介绍了锂离子电池硅基负极材料的制备方法、电化学性能及其研究现状,分析了硅材料作为锂离子电池负极材料存在的问题;讨论了硅材料作为锂离子电池负极材料的研究前景.并指出若能克服目前存在问题,将有望成为新一代锂离子电池负极材料.     

关联规则增量式更新的改进算法

关联规则是数据挖掘中的重要研究内容之一，对在事务数据库不变，只对最小支持度和最小可信度进行改变的情况下，针对关联规则的维护问题，设计了一个增量式更新的改进算法AIUA。     

基于关联规则和技术功效矩阵的企业技术创新机会发现和辅助决策方法

为助力科技型创新企业准确且快速地从外部捕获创新技术机会, 提出一种企业技术机会发现和辅助决策方法. 首先, 挖掘领域内的技术热点、技术重点和有潜力的技术作为领域技术创新机会. 然后, 通过关联规则分析领域技术机会和企业已有技术之间的相关性, 进一步结合技术掌握度和新颖度, 识别更适合企业的技术创新机会. 最后, 创新性地采用Sen-BERT语言模型和K-means聚类方法构建技术功效矩阵, 辅助企业从功能需求的角度进行技术创新决策. 以电动汽车领域为例验证了该方法的可行性.     

7-Aminoalkoxy-Quinazolines from Epigenetic Focused Libraries Are Potent and Selective Inhibitors of DNA Methyltransferase 1

Inhibitors of epigenetic writers such as DNA methyltransferases (DNMTs) are attractive compounds for epigenetic drug and probe discovery. To advance epigenetic probes and drug discovery, chemical companies are developing focused libraries for epigenetic targets. Based on a knowledge-based approach, herein we report the identification of two quinazoline-based derivatives identified in focused libraries with sub-micromolar inhibition of DNMT1 (30 and 81 nM), more potent than S-adenosylhomocysteine. Also, both compounds had a low micromolar affinity of DNMT3A and did not inhibit DNMT3B. The enzymatic inhibitory activity of DNMT1 and DNMT3A was rationalized with molecular modeling. The quinazolines reported in this work are known to have low cell toxicity and be potent inhibitors of the epigenetic target G9a. Therefore, the quinazoline-based compounds presented are attractive not only as novel potent inhibitors of DNMTs but also as dual and selective epigenetic agents targeting two families of epigenetic writers.     

Role of Intracellular Iron in Switching Apoptosis to Ferroptosis to Target Therapy-Resistant Cancer Stem Cells

Iron is a crucial element required for the proper functioning of the body. For instance, hemoglobin is the vital component in the blood that delivers oxygen to various parts of the body. The heme protein present in hemoglobin comprises iron in the form of a ferrous state which regulates oxygen delivery. Excess iron in the body is stored as ferritin and would be utilized under iron-deficient conditions. Surprisingly, cancer cells as well as cancer stem cells have elevated ferritin levels suggesting that iron plays a vital role in protecting these cells. However, apart from the cytoprotective role iron also has the potential to induce cell death via ferroptosis which is a non-apoptotic cell death dependent on iron reserves. Apoptosis a caspase-dependent cell death mechanism is effective on cancer cells however little is known about its impact on cancer stem cell death. This paper focuses on the molecular characteristics of apoptosis and ferroptosis and the importance of switching to ferroptosis to target cancer stem cells death thereby preventing cancer relapse. To the best of our knowledge, this is the first review to demonstrate the importance of intracellular iron in regulating the switching of tumor cells and therapy resistant CSCs from apoptosis to ferroptosis.     

云格环境下基于P2P的动态资源发现机制

为在云计算平台上实现大数据的高效并行处理与访问,针对动态增长的异构资源所具有的集成与共享所形成的超强计算力结合网格计算,从基于服务计算的角度分析了云计算与网格计算2个不同框架体系的集成问题,探讨了一种资源与服务的统一描述机制,提出了云格体系下的一种分组生成树的P2P网络动态资源与服务发现算法,可实现海量数据的高效处理与访问.实验表明该算法具有一定的可行性与针对性.